// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#include "main.h"

#include <Eigen/CXX11/Tensor>

using Eigen::Tensor;

void
test_simple_patch()
{
	Tensor<float, 4> tensor(2, 3, 5, 7);
	tensor.setRandom();
	Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
	VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
	VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
	VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
	VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));

	// Single pixel patch: ColMajor
	Tensor<float, 5> single_pixel_patch;
	single_pixel_patch = tensor.extract_image_patches(1, 1);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3 * 5);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(4), 7);

	// Single pixel patch: RowMajor
	Tensor<float, 5, RowMajor> single_pixel_patch_row_major;
	single_pixel_patch_row_major = tensor_row_major.extract_image_patches(1, 1);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(0), 7);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(1), 3 * 5);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(2), 1);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(3), 1);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(4), 2);

	for (int i = 0; i < tensor.size(); ++i) {
		// ColMajor
		if (tensor.data()[i] != single_pixel_patch.data()[i]) {
			std::cout << "Mismatch detected at index " << i << " : " << tensor.data()[i] << " vs "
					  << single_pixel_patch.data()[i] << std::endl;
		}
		VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
		// RowMajor
		if (tensor_row_major.data()[i] != single_pixel_patch_row_major.data()[i]) {
			std::cout << "Mismatch detected at index " << i << " : " << tensor.data()[i] << " vs "
					  << single_pixel_patch_row_major.data()[i] << std::endl;
		}
		VERIFY_IS_EQUAL(single_pixel_patch_row_major.data()[i], tensor_row_major.data()[i]);
		VERIFY_IS_EQUAL(tensor.data()[i], tensor_row_major.data()[i]);
		VERIFY_IS_EQUAL(single_pixel_patch.data()[i], single_pixel_patch_row_major.data()[i]);
	}

	// Entire image patch: ColMajor
	Tensor<float, 5> entire_image_patch;
	entire_image_patch = tensor.extract_image_patches(3, 5);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3 * 5);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(4), 7);

	// Entire image patch: RowMajor
	Tensor<float, 5, RowMajor> entire_image_patch_row_major;
	entire_image_patch_row_major = tensor_row_major.extract_image_patches(3, 5);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(0), 7);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(1), 3 * 5);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(2), 5);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(3), 3);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(4), 2);

	for (int i = 0; i < 3; ++i) {
		for (int j = 0; j < 5; ++j) {
			int patchId = i + 3 * j;
			for (int r = 0; r < 3; ++r) {
				for (int c = 0; c < 5; ++c) {
					for (int d = 0; d < 2; ++d) {
						for (int b = 0; b < 7; ++b) {
							float expected = 0.0f;
							float expected_row_major = 0.0f;
							if (r - 1 + i >= 0 && c - 2 + j >= 0 && r - 1 + i < 3 && c - 2 + j < 5) {
								expected = tensor(d, r - 1 + i, c - 2 + j, b);
								expected_row_major = tensor_row_major(b, c - 2 + j, r - 1 + i, d);
							}
							// ColMajor
							if (entire_image_patch(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId, b), expected);
							// RowMajor
							if (entire_image_patch_row_major(b, patchId, c, r, d) != expected_row_major) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(entire_image_patch_row_major(b, patchId, c, r, d), expected_row_major);
							// Check that ColMajor and RowMajor agree.
							VERIFY_IS_EQUAL(expected, expected_row_major);
						}
					}
				}
			}
		}
	}

	// 2D patch: ColMajor
	Tensor<float, 5> twod_patch;
	twod_patch = tensor.extract_image_patches(2, 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(3), 3 * 5);
	VERIFY_IS_EQUAL(twod_patch.dimension(4), 7);

	// 2D patch: RowMajor
	Tensor<float, 5, RowMajor> twod_patch_row_major;
	twod_patch_row_major = tensor_row_major.extract_image_patches(2, 2);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(0), 7);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(1), 3 * 5);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(2), 2);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(3), 2);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(4), 2);

	// Based on the calculation described in TensorTraits.h, padding happens to be 0.
	int row_padding = 0;
	int col_padding = 0;
	int stride = 1;

	for (int i = 0; i < 3; ++i) {
		for (int j = 0; j < 5; ++j) {
			int patchId = i + 3 * j;
			for (int r = 0; r < 2; ++r) {
				for (int c = 0; c < 2; ++c) {
					for (int d = 0; d < 2; ++d) {
						for (int b = 0; b < 7; ++b) {
							float expected = 0.0f;
							float expected_row_major = 0.0f;
							int row_offset = r * stride + i - row_padding;
							int col_offset = c * stride + j - col_padding;
							// ColMajor
							if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor.dimension(1) &&
								col_offset < tensor.dimension(2)) {
								expected = tensor(d, row_offset, col_offset, b);
							}
							if (twod_patch(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId, b), expected);

							// RowMajor
							if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor_row_major.dimension(2) &&
								col_offset < tensor_row_major.dimension(1)) {
								expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
							}
							if (twod_patch_row_major(b, patchId, c, r, d) != expected_row_major) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(twod_patch_row_major(b, patchId, c, r, d), expected_row_major);
							// Check that ColMajor and RowMajor agree.
							VERIFY_IS_EQUAL(expected, expected_row_major);
						}
					}
				}
			}
		}
	}
}

// Verifies VALID padding (no padding) with incrementing values.
void
test_patch_padding_valid()
{
	int input_depth = 3;
	int input_rows = 3;
	int input_cols = 3;
	int input_batches = 1;
	int ksize = 2;	// Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
	int stride = 2; // Only same stride is supported.
	Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
	// Initializes tensor with incrementing numbers.
	for (int i = 0; i < tensor.size(); ++i) {
		tensor.data()[i] = i + 1;
	}
	// ColMajor
	Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);

	VERIFY_IS_EQUAL(result.dimension(0), input_depth);	 // depth
	VERIFY_IS_EQUAL(result.dimension(1), ksize);		 // kernel rows
	VERIFY_IS_EQUAL(result.dimension(2), ksize);		 // kernel cols
	VERIFY_IS_EQUAL(result.dimension(3), 1);			 // number of patches
	VERIFY_IS_EQUAL(result.dimension(4), input_batches); // number of batches

	// RowMajor
	Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
	VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
	VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
	VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
	VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));

	Tensor<float, 5, RowMajor> result_row_major =
		tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
	VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
	VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
	VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
	VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
	VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));

	// No padding is carried out.
	int row_padding = 0;
	int col_padding = 0;

	for (int i = 0; (i + stride + ksize - 1) < input_rows; i += stride) {	  // input rows
		for (int j = 0; (j + stride + ksize - 1) < input_cols; j += stride) { // input cols
			int patchId = i + input_rows * j;
			for (int r = 0; r < ksize; ++r) {					  // patch rows
				for (int c = 0; c < ksize; ++c) {				  // patch cols
					for (int d = 0; d < input_depth; ++d) {		  // depth
						for (int b = 0; b < input_batches; ++b) { // batch
							float expected = 0.0f;
							float expected_row_major = 0.0f;
							int row_offset = r + i - row_padding;
							int col_offset = c + j - col_padding;
							if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows &&
								col_offset < input_cols) {
								expected = tensor(d, row_offset, col_offset, b);
								expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
							}
							// ColMajor
							if (result(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
							// RowMajor
							if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
							// Check that ColMajor and RowMajor agree.
							VERIFY_IS_EQUAL(expected, expected_row_major);
						}
					}
				}
			}
		}
	}
}

// Verifies VALID padding (no padding) with the same value.
void
test_patch_padding_valid_same_value()
{
	int input_depth = 1;
	int input_rows = 5;
	int input_cols = 5;
	int input_batches = 2;
	int ksize = 3;	// Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
	int stride = 2; // Only same stride is supported.
	// ColMajor
	Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
	tensor = tensor.constant(11.0f);
	Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);

	VERIFY_IS_EQUAL(result.dimension(0), input_depth);	 // depth
	VERIFY_IS_EQUAL(result.dimension(1), ksize);		 // kernel rows
	VERIFY_IS_EQUAL(result.dimension(2), ksize);		 // kernel cols
	VERIFY_IS_EQUAL(result.dimension(3), 4);			 // number of patches
	VERIFY_IS_EQUAL(result.dimension(4), input_batches); // number of batches

	// RowMajor
	Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
	VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
	VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
	VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
	VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));

	Tensor<float, 5, RowMajor> result_row_major =
		tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
	VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
	VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
	VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
	VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
	VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));

	// No padding is carried out.
	int row_padding = 0;
	int col_padding = 0;

	for (int i = 0; (i + stride + ksize - 1) <= input_rows; i += stride) {	   // input rows
		for (int j = 0; (j + stride + ksize - 1) <= input_cols; j += stride) { // input cols
			int patchId = i + input_rows * j;
			for (int r = 0; r < ksize; ++r) {					  // patch rows
				for (int c = 0; c < ksize; ++c) {				  // patch cols
					for (int d = 0; d < input_depth; ++d) {		  // depth
						for (int b = 0; b < input_batches; ++b) { // batch
							float expected = 0.0f;
							float expected_row_major = 0.0f;
							int row_offset = r + i - row_padding;
							int col_offset = c + j - col_padding;
							if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows &&
								col_offset < input_cols) {
								expected = tensor(d, row_offset, col_offset, b);
								expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
							}
							// ColMajor
							if (result(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
							// RowMajor
							if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
							// Check that ColMajor and RowMajor agree.
							VERIFY_IS_EQUAL(expected, expected_row_major);
						}
					}
				}
			}
		}
	}
}

// Verifies SAME padding.
void
test_patch_padding_same()
{
	int input_depth = 3;
	int input_rows = 4;
	int input_cols = 2;
	int input_batches = 1;
	int ksize = 2;	// Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
	int stride = 2; // Only same stride is supported.
	// ColMajor
	Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
	// Initializes tensor with incrementing numbers.
	for (int i = 0; i < tensor.size(); ++i) {
		tensor.data()[i] = i + 1;
	}
	Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, PADDING_SAME);

	VERIFY_IS_EQUAL(result.dimension(0), input_depth);	 // depth
	VERIFY_IS_EQUAL(result.dimension(1), ksize);		 // kernel rows
	VERIFY_IS_EQUAL(result.dimension(2), ksize);		 // kernel cols
	VERIFY_IS_EQUAL(result.dimension(3), 2);			 // number of patches
	VERIFY_IS_EQUAL(result.dimension(4), input_batches); // number of batches

	// RowMajor
	Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
	VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
	VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
	VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
	VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));

	Tensor<float, 5, RowMajor> result_row_major =
		tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, PADDING_SAME);
	VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
	VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
	VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
	VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
	VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));

	// Based on the calculation described in TensorTraits.h, padding happens to be
	// 0.
	int row_padding = 0;
	int col_padding = 0;

	for (int i = 0; (i + stride + ksize - 1) <= input_rows; i += stride) {	   // input rows
		for (int j = 0; (j + stride + ksize - 1) <= input_cols; j += stride) { // input cols
			int patchId = i + input_rows * j;
			for (int r = 0; r < ksize; ++r) {					  // patch rows
				for (int c = 0; c < ksize; ++c) {				  // patch cols
					for (int d = 0; d < input_depth; ++d) {		  // depth
						for (int b = 0; b < input_batches; ++b) { // batch
							float expected = 0.0f;
							float expected_row_major = 0.0f;
							int row_offset = r * stride + i - row_padding;
							int col_offset = c * stride + j - col_padding;
							if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows &&
								col_offset < input_cols) {
								expected = tensor(d, row_offset, col_offset, b);
								expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
							}
							// ColMajor
							if (result(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
							// RowMajor
							if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
							// Check that ColMajor and RowMajor agree.
							VERIFY_IS_EQUAL(expected, expected_row_major);
						}
					}
				}
			}
		}
	}
}

// Verifies that SAME padding, when computed as negative values, will be clipped
// to zero.
void
test_patch_padding_same_negative_padding_clip_to_zero()
{
	int input_depth = 1;
	int input_rows = 15;
	int input_cols = 1;
	int input_batches = 1;
	int ksize = 1; // Corresponds to the Rows and Cols for
				   // tensor.extract_image_patches<>.
	int row_stride = 5;
	int col_stride = 1;
	// ColMajor
	Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
	// Initializes tensor with incrementing numbers.
	for (int i = 0; i < tensor.size(); ++i) {
		tensor.data()[i] = i + 1;
	}
	Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, row_stride, col_stride, 1, 1, PADDING_SAME);
	// row padding will be computed as -2 originally and then be clipped to 0.
	VERIFY_IS_EQUAL(result.coeff(0), 1.0f);
	VERIFY_IS_EQUAL(result.coeff(1), 6.0f);
	VERIFY_IS_EQUAL(result.coeff(2), 11.0f);

	VERIFY_IS_EQUAL(result.dimension(0), input_depth);	 // depth
	VERIFY_IS_EQUAL(result.dimension(1), ksize);		 // kernel rows
	VERIFY_IS_EQUAL(result.dimension(2), ksize);		 // kernel cols
	VERIFY_IS_EQUAL(result.dimension(3), 3);			 // number of patches
	VERIFY_IS_EQUAL(result.dimension(4), input_batches); // number of batches

	// RowMajor
	Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
	VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
	VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
	VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
	VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));

	Tensor<float, 5, RowMajor> result_row_major =
		tensor_row_major.extract_image_patches(ksize, ksize, row_stride, col_stride, 1, 1, PADDING_SAME);
	VERIFY_IS_EQUAL(result_row_major.coeff(0), 1.0f);
	VERIFY_IS_EQUAL(result_row_major.coeff(1), 6.0f);
	VERIFY_IS_EQUAL(result_row_major.coeff(2), 11.0f);

	VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
	VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
	VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
	VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
	VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));
}

void
test_patch_no_extra_dim()
{
	Tensor<float, 3> tensor(2, 3, 5);
	tensor.setRandom();
	Tensor<float, 3, RowMajor> tensor_row_major = tensor.swap_layout();
	VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(2));
	VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(1));
	VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(0));

	// Single pixel patch: ColMajor
	Tensor<float, 4> single_pixel_patch;
	single_pixel_patch = tensor.extract_image_patches(1, 1);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
	VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3 * 5);

	// Single pixel patch: RowMajor
	Tensor<float, 4, RowMajor> single_pixel_patch_row_major;
	single_pixel_patch_row_major = tensor_row_major.extract_image_patches(1, 1);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(0), 3 * 5);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(1), 1);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(2), 1);
	VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(3), 2);

	for (int i = 0; i < tensor.size(); ++i) {
		// ColMajor
		if (tensor.data()[i] != single_pixel_patch.data()[i]) {
			std::cout << "Mismatch detected at index " << i << " : " << tensor.data()[i] << " vs "
					  << single_pixel_patch.data()[i] << std::endl;
		}
		VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
		// RowMajor
		if (tensor_row_major.data()[i] != single_pixel_patch_row_major.data()[i]) {
			std::cout << "Mismatch detected at index " << i << " : " << tensor.data()[i] << " vs "
					  << single_pixel_patch_row_major.data()[i] << std::endl;
		}
		VERIFY_IS_EQUAL(single_pixel_patch_row_major.data()[i], tensor_row_major.data()[i]);
		VERIFY_IS_EQUAL(tensor.data()[i], tensor_row_major.data()[i]);
		VERIFY_IS_EQUAL(single_pixel_patch.data()[i], single_pixel_patch_row_major.data()[i]);
	}

	// Entire image patch: ColMajor
	Tensor<float, 4> entire_image_patch;
	entire_image_patch = tensor.extract_image_patches(3, 5);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
	VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3 * 5);

	// Entire image patch: RowMajor
	Tensor<float, 4, RowMajor> entire_image_patch_row_major;
	entire_image_patch_row_major = tensor_row_major.extract_image_patches(3, 5);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(0), 3 * 5);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(1), 5);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(2), 3);
	VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(3), 2);

	for (int i = 0; i < 3; ++i) {
		for (int j = 0; j < 5; ++j) {
			int patchId = i + 3 * j;
			for (int r = 0; r < 3; ++r) {
				for (int c = 0; c < 5; ++c) {
					for (int d = 0; d < 2; ++d) {
						float expected = 0.0f;
						float expected_row_major = 0.0f;
						if (r - 1 + i >= 0 && c - 2 + j >= 0 && r - 1 + i < 3 && c - 2 + j < 5) {
							expected = tensor(d, r - 1 + i, c - 2 + j);
							expected_row_major = tensor_row_major(c - 2 + j, r - 1 + i, d);
						}
						// ColMajor
						if (entire_image_patch(d, r, c, patchId) != expected) {
							std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c
									  << " d=" << d << std::endl;
						}
						VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId), expected);
						// RowMajor
						if (entire_image_patch_row_major(patchId, c, r, d) != expected_row_major) {
							std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c
									  << " d=" << d << std::endl;
						}
						VERIFY_IS_EQUAL(entire_image_patch_row_major(patchId, c, r, d), expected_row_major);
						// Check that ColMajor and RowMajor agree.
						VERIFY_IS_EQUAL(expected, expected_row_major);
					}
				}
			}
		}
	}

	// 2D patch: ColMajor
	Tensor<float, 4> twod_patch;
	twod_patch = tensor.extract_image_patches(2, 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
	VERIFY_IS_EQUAL(twod_patch.dimension(3), 3 * 5);

	// 2D patch: RowMajor
	Tensor<float, 4, RowMajor> twod_patch_row_major;
	twod_patch_row_major = tensor_row_major.extract_image_patches(2, 2);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(0), 3 * 5);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(1), 2);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(2), 2);
	VERIFY_IS_EQUAL(twod_patch_row_major.dimension(3), 2);

	// Based on the calculation described in TensorTraits.h, padding happens to be 0.
	int row_padding = 0;
	int col_padding = 0;
	int stride = 1;

	for (int i = 0; i < 3; ++i) {
		for (int j = 0; j < 5; ++j) {
			int patchId = i + 3 * j;
			for (int r = 0; r < 2; ++r) {
				for (int c = 0; c < 2; ++c) {
					for (int d = 0; d < 2; ++d) {
						float expected = 0.0f;
						float expected_row_major = 0.0f;
						int row_offset = r * stride + i - row_padding;
						int col_offset = c * stride + j - col_padding;
						// ColMajor
						if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor.dimension(1) &&
							col_offset < tensor.dimension(2)) {
							expected = tensor(d, row_offset, col_offset);
						}
						if (twod_patch(d, r, c, patchId) != expected) {
							std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c
									  << " d=" << d << std::endl;
						}
						VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId), expected);
						// RowMajor
						if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor_row_major.dimension(1) &&
							col_offset < tensor_row_major.dimension(0)) {
							expected_row_major = tensor_row_major(col_offset, row_offset, d);
						}
						if (twod_patch_row_major(patchId, c, r, d) != expected_row_major) {
							std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c
									  << " d=" << d << std::endl;
						}
						VERIFY_IS_EQUAL(twod_patch_row_major(patchId, c, r, d), expected_row_major);
						// Check that ColMajor and RowMajor agree.
						VERIFY_IS_EQUAL(expected, expected_row_major);
					}
				}
			}
		}
	}
}

void
test_imagenet_patches()
{
	// Test the code on typical configurations used by the 'imagenet' benchmarks at
	// https://github.com/soumith/convnet-benchmarks
	// ColMajor
	Tensor<float, 4> l_in(3, 128, 128, 16);
	l_in.setRandom();
	Tensor<float, 5> l_out = l_in.extract_image_patches(11, 11);
	VERIFY_IS_EQUAL(l_out.dimension(0), 3);
	VERIFY_IS_EQUAL(l_out.dimension(1), 11);
	VERIFY_IS_EQUAL(l_out.dimension(2), 11);
	VERIFY_IS_EQUAL(l_out.dimension(3), 128 * 128);
	VERIFY_IS_EQUAL(l_out.dimension(4), 16);

	// RowMajor
	Tensor<float, 5, RowMajor> l_out_row_major = l_in.swap_layout().extract_image_patches(11, 11);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 16);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 128 * 128);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 11);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 11);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 3);

	for (int b = 0; b < 16; ++b) {
		for (int i = 0; i < 128; ++i) {
			for (int j = 0; j < 128; ++j) {
				int patchId = i + 128 * j;
				for (int c = 0; c < 11; ++c) {
					for (int r = 0; r < 11; ++r) {
						for (int d = 0; d < 3; ++d) {
							float expected = 0.0f;
							if (r - 5 + i >= 0 && c - 5 + j >= 0 && r - 5 + i < 128 && c - 5 + j < 128) {
								expected = l_in(d, r - 5 + i, c - 5 + j, b);
							}
							// ColMajor
							if (l_out(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
							// RowMajor
							if (l_out_row_major(b, patchId, c, r, d) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected);
						}
					}
				}
			}
		}
	}

	// ColMajor
	l_in.resize(16, 64, 64, 32);
	l_in.setRandom();
	l_out = l_in.extract_image_patches(9, 9);
	VERIFY_IS_EQUAL(l_out.dimension(0), 16);
	VERIFY_IS_EQUAL(l_out.dimension(1), 9);
	VERIFY_IS_EQUAL(l_out.dimension(2), 9);
	VERIFY_IS_EQUAL(l_out.dimension(3), 64 * 64);
	VERIFY_IS_EQUAL(l_out.dimension(4), 32);

	// RowMajor
	l_out_row_major = l_in.swap_layout().extract_image_patches(9, 9);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 64 * 64);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 9);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 9);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 16);

	for (int b = 0; b < 32; ++b) {
		for (int i = 0; i < 64; ++i) {
			for (int j = 0; j < 64; ++j) {
				int patchId = i + 64 * j;
				for (int c = 0; c < 9; ++c) {
					for (int r = 0; r < 9; ++r) {
						for (int d = 0; d < 16; ++d) {
							float expected = 0.0f;
							if (r - 4 + i >= 0 && c - 4 + j >= 0 && r - 4 + i < 64 && c - 4 + j < 64) {
								expected = l_in(d, r - 4 + i, c - 4 + j, b);
							}
							// ColMajor
							if (l_out(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
							// RowMajor
							if (l_out_row_major(b, patchId, c, r, d) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected);
						}
					}
				}
			}
		}
	}

	// ColMajor
	l_in.resize(32, 16, 16, 32);
	l_in.setRandom();
	l_out = l_in.extract_image_patches(7, 7);
	VERIFY_IS_EQUAL(l_out.dimension(0), 32);
	VERIFY_IS_EQUAL(l_out.dimension(1), 7);
	VERIFY_IS_EQUAL(l_out.dimension(2), 7);
	VERIFY_IS_EQUAL(l_out.dimension(3), 16 * 16);
	VERIFY_IS_EQUAL(l_out.dimension(4), 32);

	// RowMajor
	l_out_row_major = l_in.swap_layout().extract_image_patches(7, 7);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 16 * 16);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 7);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 7);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 32);

	for (int b = 0; b < 32; ++b) {
		for (int i = 0; i < 16; ++i) {
			for (int j = 0; j < 16; ++j) {
				int patchId = i + 16 * j;
				for (int c = 0; c < 7; ++c) {
					for (int r = 0; r < 7; ++r) {
						for (int d = 0; d < 32; ++d) {
							float expected = 0.0f;
							if (r - 3 + i >= 0 && c - 3 + j >= 0 && r - 3 + i < 16 && c - 3 + j < 16) {
								expected = l_in(d, r - 3 + i, c - 3 + j, b);
							}
							// ColMajor
							if (l_out(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
							// RowMajor
							if (l_out_row_major(b, patchId, c, r, d) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected);
						}
					}
				}
			}
		}
	}

	// ColMajor
	l_in.resize(64, 13, 13, 32);
	l_in.setRandom();
	l_out = l_in.extract_image_patches(3, 3);
	VERIFY_IS_EQUAL(l_out.dimension(0), 64);
	VERIFY_IS_EQUAL(l_out.dimension(1), 3);
	VERIFY_IS_EQUAL(l_out.dimension(2), 3);
	VERIFY_IS_EQUAL(l_out.dimension(3), 13 * 13);
	VERIFY_IS_EQUAL(l_out.dimension(4), 32);

	// RowMajor
	l_out_row_major = l_in.swap_layout().extract_image_patches(3, 3);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 13 * 13);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 3);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 3);
	VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 64);

	for (int b = 0; b < 32; ++b) {
		for (int i = 0; i < 13; ++i) {
			for (int j = 0; j < 13; ++j) {
				int patchId = i + 13 * j;
				for (int c = 0; c < 3; ++c) {
					for (int r = 0; r < 3; ++r) {
						for (int d = 0; d < 64; ++d) {
							float expected = 0.0f;
							if (r - 1 + i >= 0 && c - 1 + j >= 0 && r - 1 + i < 13 && c - 1 + j < 13) {
								expected = l_in(d, r - 1 + i, c - 1 + j, b);
							}
							// ColMajor
							if (l_out(d, r, c, patchId, b) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
							// RowMajor
							if (l_out_row_major(b, patchId, c, r, d) != expected) {
								std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r
										  << " c=" << c << " d=" << d << " b=" << b << std::endl;
							}
							VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected);
						}
					}
				}
			}
		}
	}
}

EIGEN_DECLARE_TEST(cxx11_tensor_image_patch)
{
	CALL_SUBTEST_1(test_simple_patch());
	CALL_SUBTEST_2(test_patch_no_extra_dim());
	CALL_SUBTEST_3(test_patch_padding_valid());
	CALL_SUBTEST_4(test_patch_padding_valid_same_value());
	CALL_SUBTEST_5(test_patch_padding_same());
	CALL_SUBTEST_6(test_imagenet_patches());
	CALL_SUBTEST_7(test_patch_padding_same_negative_padding_clip_to_zero());
}
